Methods for rapid detection and identification of bioagents for environmental and product testing

ABSTRACT

The present invention provides methods for rapid detection of bioagents for environmental and product testing. The methods can be used for testing air, water, soil, surfaces of buildings, containers, towers and the like, as well as testing of foodstuff and cosmetics.

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application is a continuation-in-part of U.S. applicationSer. No. 10/326,047 filed Dec. 18, 2002, which is a continuation-in-partof U.S. application Ser. No. 09/798,007 filed Mar. 2, 2001, each ofwhich is incorporated herein by reference in its entirety. Thisapplication also claims priority to U.S. provisional application SerialNo. 60/431,319 filed Dec. 6, 2002, and to U.S. provisional applicationSerial No. 10 60/443,788 filed Jan. 30, 2003, each of which isincorporated herein by reference in its entirety.

STATEMENT OF GOVERNMENT SUPPORT

[0002] This invention was made with United States Government supportunder DARPA/SPO contract BAA00-09. The United States Government may havecertain rights in the invention.

FIELD OF THE INVENTION

[0003] This invention relates to the field of environmental and producttesting. The invention provides rapid detection and identification ofbioagents in environmental and product samples.

BACKGROUND OF THE INVENTION

[0004] Testing for potentially harmful microbes in both natural andhuman-modified environments represents a significant public healthchallenge. Microbial contamination of waters can lead to numerousserious issues. Bacterial contamination can cause adverse economicimpacts for the affected areas by closing popular recreational areas forextended periods of time. This is particularly relevant in the heavilyvisited recreational waters and the swimming beaches in urban centers.In addition, bacterial contamination can cause severe illnesses such asgastrointestinal disorders. Microbial contaminants may not be limited tosurface or recreational waters. In fact, a far more costly migration ofthese microbial contaminants is their movement to groundwater supplieswhich are used for drinking water.

[0005] The cysts of Cryptosporidium are of increasing importance becauseof their presence in water supplies. When in the gut, fourspindle-shaped motile sporozooites burst from the cyst to infect gutepithelial cells and continue their life cycle. Entamoeba histolytica,another water-borne pathogen, can cause diarrhea or a more seriousinvasive liver abscess. When in contact with human cells, these amebaeare cytotoxic. Giardia is found in contaminated rivers and lakes and isalso be contracted via contaminated foods. There is some evidence that aheavy infection of attached Giardia physically blocks the importanttransport of nutrients across the epithelium (see, for example,www.cellsalive.com/parasit.htm).

[0006] Detection of airborne pathogens has also garnered much attentionin light of the recent anthrax attack where anthrax spores weredisseminated from mail packages.

[0007] A recent news report has stated that the anthrax mailed to aSenate office last fall was able to become airborne again even after itsettled in the office. The fact that ordinary movement in the office wasenough to send anthrax back into the air provides evidence that thespores were altered to make them more dangerous. Scientists thought thatonce the anthrax-laden envelope was opened, the spores would settle inthe office and would be unlikely to become airborne again. Butsimulation of normal workplace activities such as paper handling,walking around the office and mail sorting several weeks after theenvelope arrived, caused the spores to become airborne. Measurements ofanthrax in the air of the office were substantially higher afterresearchers simulated everyday office activity than when the office wasmore still. And more than 80% of the airborne anthrax spores were of asize that could easily be breathed into the lungs (see, for example,www.ph.ucla.edu/epi/bioter/officeactivityanthrax.html).

[0008] According to a study published in 1999 by the Centers for DiseaseControl and Prevention (Atlanta), there were almost 14 million cases offoodborne illness caused by known pathogenic microbes (bacteria,parasites, and viruses) in the United States in 1997, and theseillnesses caused more than 60,000 hospitalizations and almost 2000deaths (1). Although ˜70% of the reported illnesses were caused by foodcontaminated with Norwalk-like viruses, almost half of the deaths werethe result of infection with Listeria monocytogenes and Salmonellaspecies bacteria. Foodborne microbial contamination comes in a varietyof guises and from myriad sources. Perhaps the best-known foodbomeillnesses come from the various subspecies of E. coli. Largelyassociated with raw or undercooked ground beef, E coli. infection leadsto gastrointestinal disorders. Infection is usually self-limited and canlast for about eight days. In some cases, however, infection can lead tohemolytic uremic syndrome, which causes renal failure and anemia, and itcan be deadly to children, the elderly, and those with weakened immunesystems. Certain subtypes of E. coli can cause severe, even lethalillness. For example, in the spring of 1992-93, a multi-state outbreakof over 500 cases of E. coli O157:H7 infections was associated with arestaurant chain (www.dhss.state.mo.us/MoEpi/moepi161.pdf).

[0009] One of the least understood but increasingly prevalent illnessesis caused by Listeria monocytogenes. Associated with raw milk, softcheeses, and raw meats, L. monocytogenes infection can lead tomeningitis, encephalitis, and intrauterine or cervical infections inpregnant women that can cause spontaneous abortion or stillbirth.Listeria is able to grow under a wide variety of conditions, includingrefrigeration.

[0010] Another common infection is caused by Salmonella species.Associated with raw meats, poultry, and eggs, Salmonella infection canlead to nausea, vomiting, cramps, and diarrhea. Typically, acutesymptoms subside after a couple of days. In severe cases of S. typhi orparatyphi, however, infection can cause a typhoid-like fever andpossible septicemia.

[0011] As with many other bacteria, Campylobacter jejuni infections alsolead to gastrointestinal disorders. Infection is usually self-limitingand lasts 7-10 days. Associated largely with poultry, Campylobacter isalso found in unchlorinated water but can be eliminated by boiling.

[0012] The family of Norwalk-like viruses (NLVs) is spread throughfeces-contaminated water, and are thus largely associated withshellfish. Although most people have been exposed to NLVs at some pointin their lives, they rarely exhibit any symptoms. Disease associatedwith infection is usually mild, with symptoms of vomiting, nausea, andabdominal pain, but infection is usually self-limiting and symptomssubside within 2 days.

[0013] Corporations and government health officials have put much effortinto food testing to prevent human suffering and avoid lawsuits. The twobig challenges to large-scale testing of samples, both during foodprocessing and from a clinical perspective, are time and sensitivity.Traditional microbiological methods require that the microbes becultured and characterized for a variety of metabolic and physicalmarkers. This process can take days to weeks, depending on the organism.For example, in a test to detect Salmonella, one bacterialpre-enrichment step takes 16-20 h, a Salmonella-specific enrichmenttakes another 24 h, and a final identification step in which culturesare streaked out onto selective media can take 24-48 h. If the resultsare positive, they must then be confirmed by sub-cultivation andserological testing. Thus, this assay can take anywhere from 3 to 6days. During this time, the food products might decay beyond the sellingpoint. Consumers might contract food poisoning from the products,putting them at risk for sickness or death. It is therefore preferableto have an assay that can locate and identify the offending microbes ina timeframe that is measured in hours, not days.

[0014] Similarly, the assay must also be very sensitive because thetested samples might have no more (and possibly less) than one cell permilliliter or gram of starting material. Listeria infections can startfrom as few as 10 cells. As with most traditional microbiological tests,this requires some form of microbe culture enrichment using a growthmedium, but it is critical that this step not take too much time (see,for example,pubs.acs.org/subscribe/journals/tcaw/12/i03/pdf/303willis.pdf).

[0015] Bacteria and their enzymes, along with some fungi and criticalnutrient additives are cost effective agents for in-situ remediation(otherwise known as bioremediation) of hazardous wastes and subsurfacepollution in soils, sediments and wastewaters. The ability of eachbacterial strain to degrade toxic waste depends on the nature of eachcontaminant. Since most sites are typically comprised of multiplepollutant types, the most effective approach to bioremediation is to usea mixture of bacterial species/strains, each specific to the degradationof one or more types of contaminants. It is critical to monitor thecomposition of the indigenous and added bacterial consortium in order toevaluate the activity level of the bacteria, and to permit modificationsof the nutrients and other conditions for optimizing the bioremediationprocess. Additionally, it is desirable to return a bioremediation siteto its natural state following the bioremediation process. Thus,monitoring of levels of bioremediating bacteria becomes necessary inassessment of the return of the site to the natural state. Fungalbioremediation is also possible. This technology utilizes white-rotfungi to clean up a wide spectrum of soil pollutants, such as woodpreservatives, polycyclic aromatic hydrocarbons, organochlorines,polychlorinated biphyenyls, dyes, pesticides, fungicides, herbicides,and others. Rapid throughput methods for detection and identification ofthe members of the indigenous and added bacterial and/or fungalconsortium would greatly facilitate characterization of suchbioremediative processes.

[0016] Household mold, is a growing concern for homeowners. Molds notonly pose serious threats to a home's construction and survival, theypose serious threats to one's health. More than 100,000 types of moldshave been discovered yet little is known about the life of these moldsand their allergens, and how they become airborne.

[0017] Stachybotrys is a species of mold which has earned the title“toxic black mold,” as it is one of the most lethal, yet common forms.Stachybotrys can become airborne and cause serious respiratorydifficulties, memory and hearing loss, hemorrhaging, dizziness andsometimes death. Prolonged exposure to this strain can impair memory.

[0018] Cladosporium, Penicillium and Alternaria are more frequentlydetected in household mold problems. While not as likely to pose a fatalthreat, these molds are known for causing asthma-related symptoms.Studies suggest that such molds are culpable for, or at least connectedto, the tripled asthma rate in the past 20 years (see, for example,www.paloaltoonline.com/paw/paonline/news_features/real_estate/spring2002/2002_(—)03_(—)13.mold.shtml).

[0019] Identification of species of molds would also benefit from arapid method for detection and identification.

[0020] Mass spectrometry provides detailed information about themolecules being analyzed, including high mass accuracy. It is also aprocess that can be easily automated. Low-resolution MS may beunreliable when used to detect some known agents, if their spectrallines are sufficiently weak or sufficiently close to those from otherliving organisms in the sample. DNA chips with specific probes can onlydetermine the presence or absence of specifically anticipated organisms.Because there are hundreds of thousands of species of benign bacteria,some very similar in sequence to threat organisms, even arrays with10,000 probes lack the breadth needed to detect a particular organism.

[0021] Antibodies face more severe diversity limitations than arrays. Ifantibodies are designed against highly conserved targets to increasediversity, the false alarm problem will dominate, again because threatorganisms are very similar to benign ones. Antibodies are only capableof detecting known agents in relatively uncluttered environments.

[0022] Several groups have described detection of PCR products usinghigh resolution electrospray ionization-Fourier transform-ion cyclotronresonance mass spectrometry (ESI-FT-ICR MS). Accurate measurement ofexact mass combined with knowledge of the number of at least onenucleotide allowed calculation of the total base composition for PCRduplex products of approximately 100 base pairs. (Aaserud et al., J. Am.Soc. Mass Spec., 1996, 7, 1266-1269; Muddiman et al., Anal. Chem., 1997,69, 1543-1549; Wunschel et al., Anal. Chem., 1998, 70, 1203-1207;Muddiman et al., Rev. Anal. Chem., 1998, 17, 1-68). Electrosprayionization-Fourier transform-ion cyclotron resistance (ESI-FT-ICR) MSmay be used to determine the mass of double-stranded, 500 base-pair PCRproducts via the average molecular mass (Hurst et al., Rapid Commun.Mass Spec. 1996, 10, 377-382). The use of matrix-assisted laserdesorption ionization-time of flight (MALDI-TOF) mass spectrometry forcharacterization of PCR products has been described. (Muddiman et al.,Rapid Commun. Mass Spec., 1999, 13, 1201-1204). However, the degradationof DNAs over about 75 nucleotides observed with MALDI limited theutility of this method.

[0023] U.S. Pat. No. 5,849,492 describes a method for retrieval ofphylogenetically informative DNA sequences which comprise searching fora highly divergent segment of genomic DNA surrounded by two highlyconserved segments, designing the universal primers for PCRamplification of the highly divergent region, amplifying the genomic DNAby PCR technique using universal primers, and then sequencing the geneto determine the identity of the organism.

[0024] U.S. Pat. No. 5,965,363 discloses methods for screening nucleicacids for polymorphisms by analyzing amplified target nucleic acidsusing mass spectrometric techniques and to procedures for improving massresolution and mass accuracy of these methods.

[0025] WO 99/14375 describes methods, PCR primers and kits for use inanalyzing preselected DNA tandem nucleotide repeat alleles by massspectrometry.

[0026] WO 98/12355 discloses methods of determining the mass of a targetnucleic acid by mass spectrometric analysis, by cleaving the targetnucleic acid to reduce its length, making the target single-stranded andusing MS to determine the mass of the single-stranded shortened target.Also disclosed are methods of preparing a double-stranded target nucleicacid for MS analysis comprising amplification of the target nucleicacid, binding one of the strands to a solid support, releasing thesecond strand and then releasing the first strand which is then analyzedby MS. Kits for target nucleic acid preparation are also provided.

[0027] PCT W097/33000 discloses methods for detecting mutations in atarget nucleic acid by nonrandomly fragmenting the target into a set ofsingle-stranded nonrandom length fragments and determining their massesby MS.

[0028] U.S. Pat. No. 5,605,798 describes a fast and highly accurate massspectrometer-based process for detecting the presence of a particularnucleic acid in a biological sample for diagnostic purposes.

[0029] WO 98/21066 describes processes for determining the sequence of aparticular target nucleic acid by mass spectrometry. Processes fordetecting a target nucleic acid present in a biological sample by PCRamplification and mass spectrometry detection are disclosed, as aremethods for detecting a target nucleic acid in a sample by amplifyingthe target with primers that contain restriction sites and tags,extending and cleaving the amplified nucleic acid, and detecting thepresence of extended product, wherein the presence of a DNA fragment ofa mass different from wild-type is indicative of a mutation. Methods ofsequencing a nucleic acid via mass spectrometry methods are alsodescribed.

[0030] WO 97/37041, WO 99/31278 and U.S. Pat. No. 5,547,835 describemethods of sequencing nucleic acids using mass spectrometry. U.S. Pat.Nos. 5,622,824, 5,872,003 and 5,691,141 describe methods, systems andkits for exonuclease-mediated mass spectrometric sequencing.

[0031] Thus, there is a need for a method for bioagent detection andidentification which is both specific and rapid, and in which no nucleicacid sequencing is required. The present invention addresses this need.

SUMMARY OF THE INVENTION

[0032] The present invention is directed to methods of identifying abioagent in a sample by determining a first molecular mass of a firstamplification product of a first bioagent identifying amplicon from thesample and comparing the first molecular mass to a second molecular massof a second bioagent identifying amplicon wherein both first and secondbioagent identifying amplicons are correlative. These methods areapplicable to environmental samples including, for example, air samples,water samples, soil samples, surface swab samples and samples from abuilding or a container. These methods are also applicable to productsamples including, for example, foodstuff and cosmetic samples.

[0033] The present invention is also directed to methods of monitoring abioremediation process by identifying bioagents in a sample bydetermining a first molecular mass of a first amplification product of afirst bioagent identifying amplicon from the sample and comparing thefirst molecular mass to a second molecular mass of a second bioagentidentifying amplicon wherein both first and second bioagent identifyingamplicons are correlative.

BRIEF DESCRIPTION OF THE DRAWINGS

[0034]FIGS. 1A-1H and FIG. 2 are consensus diagrams that show examplesof conserved regions from 16S rRNA (FIG. 1A-1, 1A-2, 1A-3, 1A-4, and1A-5), 23S rRNA (3′-half, FIG. 1B, 1C, and 1D; 5′-half, FIG. 1E-F), 23SrRNA Domain I (FIG. 1G), 23S rRNA Domain IV (FIG. 1H) and 16S rRNADomain III (FIG. 2) which are suitable for use in the present invention.Lines with arrows are examples of regions to which intelligent primerpairs for PCR are designed. The label for each primer pair representsthe starting and ending base number of the amplified region on theconsensus diagram. Bases in capital letters are greater than 95%conserved; bases in lower case letters are 90-95% conserved, filledcircles are 80-90% conserved; and open circles are less than 80%conserved. The label for each primer pair represents the starting andending base number of the amplified region on the consensus diagram. Thenucleotide sequence of the 16S rRNA consensus sequence is SEQ ID NO:3and the nucleotide sequence of the 23S rRNA consensus sequence is SEQ IDNO:4.

[0035]FIG. 2 shows a typical primer amplified region from the 16S rRNADomain III shown in FIG. 1A-1.

[0036]FIG. 3 is a schematic diagram showing conserved regions in RNaseP. Bases in capital letters are greater than 90% conserved; bases inlower case letters are 80-90% conserved; filled circles designate baseswhich are 70-80% conserved; and open circles designate bases that areless than 70% conserved.

[0037]FIG. 4 is a schematic diagram of base composition signaturedetermination using nucleotide analog “tags” to determine basecomposition signatures.

[0038]FIG. 5 shows the deconvoluted mass spectra of a Bacillus anthracisregion with and without the mass tag phosphorothioate A (A*). The twospectra differ in that the measured molecular weight of the masstag-containing sequence is greater than the unmodified sequence.

[0039]FIG. 6 shows base composition signature (BCS) spectra from PCRproducts from Staphylococcus aureus (S. aureus 16S_(—)1337F) andBacillus anthracis (B. anthr. 16S_(—)1337F), amplified using the sameprimers. The two strands differ by only two (AT→CG) substitutions andare clearly distinguished on the basis of their BCS.

[0040]FIG. 7 shows that a single difference between two sequences (A14in B. anthracis vs. A15 in B. cereus) can be easily detected usingESI-TOF mass spectrometry.

[0041]FIG. 8 is an ESI-TOF of Bacillus anthracis spore coat protein sspE56mer plus calibrant. The signals unambiguously identify B. anthracisversus other Bacillus species.

[0042]FIG. 9 is an ESI-TOF of a B. anthracis synthetic 16S_(—)1228duplex (reverse and forward strands). The technique easily distinguishesbetween the forward and reverse strands.

[0043]FIG. 10 is an ESI-FTICR-MS of a synthetic B. anthracis 16S_(—)133746 base pair duplex.

[0044]FIG. 11 is an ESI-TOF-MS of a 56mer oligonucleotide (3 scans) fromthe B. anthracis saspB gene with an internal mass standard. The internalmass standards are designated by asterisks.

[0045]FIG. 12 is an ESI-TOF-MS of an internal standard with 5 mM TBA-TFAbuffer showing that charge stripping with tributylammoniumtrifluoroacetate reduces the most abundant charge state from [M−8H+]8−to[M−3H+]3−.

[0046]FIG. 13 is a portion of a secondary structure defining databaseaccording to one embodiment of the present invention, where two examplesof selected sequences are displayed graphically thereunder.

[0047]FIG. 14 is a three dimensional graph demonstrating the grouping ofsample molecular weight according to species.

[0048]FIG. 15 is a three dimensional graph demonstrating the grouping ofsample molecular weights according to species of virus and mammalinfected.

[0049]FIG. 16 is a three dimensional graph demonstrating the grouping ofsample molecular weights according to species of virus, andanimal-origin of infectious agent.

[0050]FIG. 17 is a figure depicting how the triangulation method of thepresent invention provides for the identification of an unknown bioagentwithout prior knowledge of the unknown agent. The use of differentprimer sets to distinguish and identify the unknown is also depicted asprimer sets I, II and III within this figure. A three dimensional graphdepicts all of bioagent space (170), including the unknown bioagent,which after use of primer set I (171) according to a method according tothe present invention further differentiates and classifies bioagentsaccording to major classifications (176) which, upon further analysisusing primer set II (172) differentiates the unknown agent (177) fromother, known agents (173) and finally, the use of a third primer set(175) further specifies subgroups within the family of the unknown(174).

[0051]FIG. 18 shows a representative mass spectra from amplicons derivedfrom a single primer pair used in a dilution to extinction experimentwith Bti spores as described. The concentration of spores is shown atthe right of each spectrum. Positive and negative strands are labeled.

[0052]FIG. 19 shows a representative ROC curve demonstrating that airsamples spiked with a spore sample are identified and detectable abovebackground bioagents by using the present methods.

DESCRIPTION OF EMBODIMENTS

[0053] A. Introduction

[0054] The present invention provides, inter alia, methods for detectionand identification of bioagents in an unbiased manner using “bioagentidentifying amplicons.” “Intelligent primers” are selected to hybridizeto conserved sequence regions of nucleic acids derived from a bioagentand which bracket variable sequence regions to yield a bioagentidentifying amplicon which can be amplified and which is amenable tomolecular mass determination. The molecular mass then provides a meansto uniquely identify the bioagent without a requirement for priorknowledge of the possible identity of the bioagent. The molecular massor corresponding “base composition signature” (BCS) of the amplificationproduct is then matched against a database of molecular masses or basecomposition signatures. Furthermore, the method can be applied to rapidparallel “multiplex” analyses, the results of which can be employed in atriangulation identification strategy. The present method provides rapidthroughput and does not require nucleic acid sequencing of the amplifiedtarget sequence for bioagent detection and identification.

[0055] B. Bioagents

[0056] In the context of this invention, a “bioagent” is any organism,cell, or virus, living or dead, or a nucleic acid derived from such anorganism, cell or virus. Examples of bioagents include, but are notlimited, to cells, including but not limited to, cells, including butnot limited to human clinical samples, bacterial cells and otherpathogens) viruses, fungi, and protists, parasites, and pathogenicitymarkers (including but not limited to: pathogenicity islands, antibioticresistance genes, virulence factors, toxin genes and other bioregulatingcompounds). Samples may be alive or dead or in a vegetative state (forexample, vegetative bacteria or spores) and may be encapsulated orbioengineered. In the context of this invention, a “pathogen” is abioagent which causes a disease or disorder.

[0057] Despite enormous biological diversity, all forms of life on earthshare sets of essential, common features in their genomes. Bacteria, forexample have highly conserved sequences in a variety of locations ontheir genomes. Most notable is the universally conserved region of theribosome. but there are also conserved elements in other non-codingRNAs, including RNAse P and the signal recognition particle (SRP) amongothers. Bacteria have a common set of absolutely required genes. About250 genes are present in all bacterial species (Proc. Natl. Acad. Sci.U.S.A., 1996, 93, 10268; Science, 1995, 270, 397), including tinygenomes like Mycoplasma, Ureaplasma and Rickettsia. These genes encodeproteins involved in translation, replication, recombination and repair,transcription, nucleotide metabolism, amino acid metabolism, lipidmetabolism, energy generation, uptake, secretion and the like. Examplesof these proteins are DNA polymerase III beta, elongation factor TU,heat shock protein groEL, RNA polymerase beta, phosphoglycerate kinase,NADH dehydrogenase, DNA ligase, DNA topoisomerase and elongation factorG. Operons can also be targeted using the present method. One example ofan operon is the bfp operon from enteropathogenic E. coli. Multiple corechromosomal genes can be used to classify bacteria at a genus or genusspecies level to determine if an organism has threat potential. Themethods can also be used to detect pathogenicity markers (plasmid orchromosomal) and antibiotic resistance genes to confirm the threatpotential of an organism and to direct countermeasures.

[0058] C. Selection of “Bioagent Identifying Amplicons”

[0059] Since genetic data provide the underlying basis foridentification of bioagents by the methods of the present invention, itis necessary to select segments of nucleic acids which ideally provideenough variability to distinguish each individual bioagent and whosemolecular mass is amenable to molecular mass determination. In oneembodiment of the present invention, at least one polynucleotide segmentis amplified to facilitate detection and analysis in the process ofidentifying the bioagent. Thus, the nucleic acid segments which provideenough variability to distinguish each individual bioagent and whosemolecular masses are amenable to molecular mass determination are hereindescribed as “bioagent identifying amplicons.” The term “amplicon” asused herein, refers to a segment of a polynucleotide which is amplifiedin an amplification reaction.

[0060] As used herein, “intelligent primers” are primers that aredesigned to bind to highly conserved sequence regions of a bioagentidentifying amplicon that flank an intervening variable region and yieldamplification products which ideally provide enough variability todistinguish each individual bioagent, and which are amenable tomolecular mass analysis. By the term “highly conserved,” it is meantthat the sequence regions exhibit between about 80-100%, or betweenabout 90-100%, or between about 95-100% identity. The molecular mass ofa given amplification product provides a means of identifying thebioagent from which it was obtained, due to the variability of thevariable region. Thus design of intelligent primers requires selectionof a variable region with appropriate variability to resolve theidentity of a given bioagent. Bioagent identifying amplicons are ideallyspecific to the identity of the bioagent. A plurality of bioagentidentifying amplicons selected in parallel for distinct bioagents whichcontain the same conserved sequences for hybridization of the same pairof intelligent primers are herein defined as “correlative bioagentidentifying amplicons.”

[0061] In one embodiment, the bioagent identifying amplicon is a portionof a ribosomal RNA (rRNA) gene sequence. With the complete sequences ofmany of the smallest microbial genomes now available, it is possible toidentify a set of genes that defines “minimal life”and identifycomposition signatures that uniquely identify each gene and organism.Genes that encode core life functions such as DNA replication,transcription, ribosome structure, translation, and transport aredistributed broadly in the bacterial genome and are suitable regions forselection of bioagent identifying amplicons. Ribosomal RNA (rRNA) genescomprise regions that provide useful base composition signatures. Likemany genes involved in core life functions, rRNA genes contain sequencesthat are extraordinarily conserved across bacterial domains interspersedwith regions of high variability that are more specific to each species.The variable regions can be utilized to build a database of basecomposition signatures. The strategy involves creating a structure-basedalignment of sequences of the small (16S) and the large (23S) subunitsof the rRNA genes. For example, there are currently over 13,000sequences in the ribosomal RNA database that has been created andmaintained by Robin Gutell, University of Texas at Austin, and ispublicly available on the Institute for Cellular and Molecular Biologyweb page on the world wide web of the Internet at, for example,“rna.icmb.utexas.edu/.” There is also a publicly available rRNA databasecreated and maintained by the University of Antwerp, Belgium on theworld wide web of the Internet at, for example, “rrna.uia.ac.be.”

[0062] These databases have been analyzed to determine regions that areuseful as bioagent identifying amplicons. The characteristics of suchregions include: a) between about 80 and 100%, or greater than about 95%identity among species of the particular bioagent of interest, ofupstream and downstream nucleotide sequences which serve as sequenceamplification primer sites; b) an intervening variable region whichexhibits no greater than about 5% identity among species; and c) aseparation of between about 30 and 1000 nucleotides, or no more thanabout 50-250 nucleotides, or no more than about 60-100 nucleotides,between the conserved regions.

[0063] As a non-limiting example, for identification of Bacillusspecies, the conserved sequence regions of the chosen bioagentidentifying amplicon must be highly conserved among all Bacillus specieswhile the variable region of the bioagent identifying amplicon issufficiently variable such that the molecular masses of theamplification products of all species of Bacillus are distinguishable.

[0064] Bioagent identifying amplicons amenable to molecular massdetermination are either of a length, size or mass compatible with theparticular mode of molecular mass 10 determination or compatible with ameans of providing a predictable fragmentation pattern in order toobtain predictable fragments of a length compatible with the particularmode of molecular mass determination. Such means of providing apredictable fragmentation pattern of an amplification product include,but are not limited to, cleavage with restriction enzymes or cleavageprimers, for example.

[0065] Identification of bioagents can be accomplished at differentlevels using intelligent primers suited to resolution of each individuallevel of identification. “Broad range survey” intelligent primers aredesigned with the objective of identifying a bioagent as a member of aparticular division of bioagents. A “bioagent division” is defined asgroup of bioagents above the species level and includes but is notlimited to: orders, families, classes, clades, genera or other suchgroupings of bioagents above the species level. As a non-limitingexample, members of the Bacillus/Clostridia group orgamma-proteobacteria group may be identified as such by employing broadrange survey intelligent primers such as primers which target 16S or 23Sribosomal RNA.

[0066] In some embodiments, broad range survey intelligent primers arecapable of identification of bioagents at the species level. One mainadvantage of the detection methods of the present invention is that thebroad range survey intelligent primers need not be specific for aparticular bacterial species, or even genus, such as Bacillus orStreptomyces. Instead, the primers recognize highly conserved regionsacross hundreds of bacterial species including, but not limited to, thespecies described herein. Thus, the same broad range survey intelligentprimer pair can be used to identify any desired bacterium because itwill bind to the conserved regions that flank a variable region specificto a single species, or common to several bacterial species, allowingunbiased nucleic acid amplification of the intervening sequence anddetermination of its molecular weight and base composition. For example,the 16S_(—)971-1062, 16S_(—)1228-1310 and 16S_(—)1100-1188 regions are98-99% conserved in about 900 species of bacteria (16S=16S rRNA, numbersindicate nucleotide position). In one embodiment of the presentinvention, primers used in the present method bind to one or more ofthese regions or portions thereof.

[0067] Due to their overall conservation, the flanking rRNA primersequences serve as good intelligent primer binding sites to amplify thenucleic acid region of interest for most, if not all, bacterial species.The intervening region between the sets of primers varies in lengthand/or composition, and thus provides a unique base compositionsignature. Examples of intelligent primers that amplify regions of the16S and 23S rRNA are shown in FIGS. 1A-1H. A typical primer amplifiedregion in 16S rRNA is shown in FIG. 2. The arrows represent primers thatbind to highly conserved regions which flank a variable region in 16SrRNA domain III. The amplified region is the stem-loop structure under“1100-1188.”It is advantageous to design the broad range surveyintelligent primers to minimize the number of primers required for theanalysis, and to allow detection of multiple members of a bioagentdivision using a single pair of primers. The advantage of using broadrange survey intelligent primers is that once a bioagent is broadlyidentified, the process of further identification at species andsub-species levels is facilitated by directing the choice of additionalintelligent primers.

[0068] “Division-wide” intelligent primers are designed with anobjective of identifying a bioagent at the species level. As anon-limiting example, a Bacillus anthracis, Bacillus cereus and Bacillusthuringiensis can be distinguished from each other using division-wideintelligent primers. Division-wide intelligent primers are not alwaysrequired for identification at the species level because broad rangesurvey intelligent primers may provide sufficient identificationresolution to accomplishing this identification objective.

[0069] “Drill-down” intelligent primers are designed with an objectiveof identifying a sub-species characteristic of a bioagent. A“sub-species characteristic” is defined as a property imparted to abioagent at the sub-species level of identification as a result of thepresence or absence of a particular segment of nucleic acid. Suchsub-species characteristics include, but are not limited to, strains,sub-types, pathogenicity markers such as antibiotic resistance genes,pathogenicity islands, toxin genes and virulence factors. Identificationof such sub-species characteristics is often critical for determiningproper clinical treatment of pathogen infections.

[0070] Chemical Modifications of Intelligent Primers

[0071] Ideally, intelligent primer hybridization sites are highlyconserved in order to facilitate the hybridization of the primer. Incases where primer hybridization is less efficient due to lower levelsof conservation of sequence, intelligent primers can be chemicallymodified to improve the efficiency of hybridization.

[0072] For example, because any variation (due to codon wobble in the3^(rd) position) in these conserved regions among species is likely tooccur in the third position of a DNA triplet, oligonucleotide primerscan be designed such that the nucleotide corresponding to this positionis a base which can bind to more than one nucleotide, referred to hereinas a “universal base.” For example, under this “wobble” pairing, inosine(I) binds to U, C or A; guanine (G) binds to U or C, and uridine (U)binds to U or C. Other examples of universal bases include nitroindolessuch as 5-nitroindole or 3-nitropyrrole (Loakes et al., Nucleosides andNucleotides, 1995, 14, 1001-1003), the degenerate nucleotides dP or dK(Hill et al.), an acyclic nucleoside analog containing 5-nitroindazole(Van Aerschot et al., Nucleosides and Nucleotides, 1995, 14, 1053-1056)or the purine analog1-(2-deoxy-β-D-ribofuranosyl)-imidazole-4-carboxamide (Sala et al.,Nucl. Acids Res., 1996, 24, 3302-3306).

[0073] In another embodiment of the invention, to compensate for thesomewhat weaker binding by the “wobble” base, the oligonucleotideprimers are designed such that the first and second positions of eachtriplet are occupied by nucleotide analogs which bind with greateraffinity than the unmodified nucleotide. Examples of these analogsinclude, but are not limited to, 2,6-diaminopurine which binds tothymine, propyne T which binds to adenine and propyne C andphenoxazines, including G-clamp, which binds to G. Propynylatedpyrimidines are described in U.S. Pat. Nos. 5,645,985, 5,830,653 and5,484,908, each of which is commonly owned and incorporated herein byreference in its entirety. Propynylated primers are claimed in U.S. Ser.No. 10/294,203 which is also commonly owned and incorporated herein byreference in entirety. Phenoxazines are described in U.S. Pat. Nos.5,502,177, 5,763,588, and 6,005,096, each of which is incorporatedherein by reference in its entirety. G-clamps are described in U.S. Pat.Nos. 6,007,992 and 6,028,183, each of which is incorporated herein byreference in its entirety.

[0074] D. Characterization of Bioagent Identifying Amplicons

[0075] A theoretically ideal bioagent detector would identify, quantify,and report the complete nucleic acid sequence of every bioagent thatreached the sensor. The complete sequence of the nucleic acid componentof a pathogen would provide all relevant information about the threat,including its identity and the presence of drug-resistance orpathogenicity markers. This ideal has not yet been achieved. However,the present invention provides a straightforward strategy for obtaininginformation with the same practical value based on analysis of bioagentidentifying amplicons by molecular mass determination.

[0076] In some cases, a molecular mass of a given bioagent identifyingamplicon alone does not provide enough resolution to unambiguouslyidentify a given bioagent. For example, the molecular mass of thebioagent identifying amplicon obtained using the intelligent primer pair“16S_(—)971” would be 55622 Da for both E. coli and Salmonellatyphimurium. However, if additional intelligent primers are employed toanalyze additional bioagent identifying amplicons, a “triangulationidentification” process is enabled. For example, the “16S_(—)1100”intelligent primer pair yields molecular masses of 55009 and 55005 Dafor E. coli and Salmonella typhimurium, respectively. Furthermore, the“23S_(—)855” intelligent primer pair yields molecular masses of 42656and 42698 Da for E. coli and Salmonella typhimurium, respectively. Inthis basic example, the second and third intelligent primer pairsprovided the additional “fingerprinting” capability or resolution todistinguish between the two bioagents.

[0077] In another embodiment, the triangulation identification processis pursued by measuring signals from a plurality of bioagent identifyingamplicons selected within multiple core genes. This process is used toreduce false negative and false positive signals, and enablereconstruction of the origin of hybrid or otherwise engineeredbioagents. In this process, after identification of multiple core genes,alignments are created from nucleic acid sequence databases. Thealignments are then analyzed for regions of conservation and variation,and bioagent identifying amplicons are selected to distinguish bioagentsbased on specific genomic differences. For example, identification ofthe three part toxin genes typical of B. anthracis (Bowen et al., J.Appl. Microbiol., 1999, 87, 270-278) in the absence of the expectedsignatures from the B. anthracis genome would suggest a geneticengineering event.

[0078] The triangulation identification process can be pursued bycharacterization of bioagent identifying amplicons in a massivelyparallel fashion using the polymerase chain reaction (PCR), such asmultiplex PCR, and mass spectrometric (MS) methods. Sufficientquantities of nucleic acids should be present for detection of bioagentsby MS. A wide variety of techniques for preparing large amounts ofpurified nucleic acids or fragments thereof are well known to those ofskill in the art. PCR requires one or more pairs of oligonucleotideprimers that bind to regions which flank the target sequence(s) to beamplified. These primers prime synthesis of a different strand of DNA,with synthesis occurring in the direction of one primer towards theother primer. The primers, DNA to be amplified, a thermostable DNApolymerase (e.g. Taq polymerase), the four deoxynucleotidetriphosphates, and a buffer are combined to initiate DNA synthesis. Thesolution is denatured by heating, then cooled to allow annealing ofnewly added primer, followed by another round of DNA synthesis. Thisprocess is typically repeated for about 30 cycles, resulting inamplification of the target sequence.

[0079] Although the use of PCR is suitable, other nucleic acidamplification techniques may also be used, including ligase chainreaction (LCR) and strand displacement amplification (SDA). Thehigh-resolution MS technique allows separation of bioagent spectrallines from background spectral lines in highly cluttered environments.

[0080] In another embodiment, the detection scheme for the PCR productsgenerated from the bioagent(s) incorporates at least three features.First, the technique simultaneously detects and differentiates multiple(generally about 6-10) PCR products. Second, the technique provides amolecular mass that uniquely identifies the bioagent from the possibleprimer sites. Finally, the detection technique is rapid, allowingmultiple PCR reactions to be run in parallel.

[0081] E. Mass Spectrometric Characterization of Bioagent IdentifyingAmplicons

[0082] Mass spectrometry (MS)-based detection of PCR products provides ameans for determination of BCS which has several advantages. MS isintrinsically a parallel detection scheme without the need forradioactive or fluorescent labels, since every amplification product isidentified by its molecular mass. The current state of the art in massspectrometry is such that less than femtomole quantities of material canbe readily analyzed to afford information about the molecular contentsof the sample. An accurate assessment of the molecular mass of thematerial can be quickly obtained, irrespective of whether the molecularweight of the sample is several hundred, or in excess of one hundredthousand atomic mass units (amu) or Daltons. Intact molecular ions canbe generated from amplification products using one of a variety ofionization techniques to convert the sample to gas phase. Theseionization methods include, but are not limited to, electrosprayionization (ES), matrix-assisted laser desorption ionization (MALDI) andfast atom bombardment (FAB). For example, MALDI of nucleic acids, alongwith examples of matrices for use in MALDI of nucleic acids, aredescribed in WO 98/54751 (Genetrace, Inc.).

[0083] In some embodiments, large DNAs and RNAs, or large amplificationproducts therefrom, can be digested with restriction endonucleases priorto ionization. Thus, for example, an amplification product that was 10kDa could be digested with a series of restriction endonucleases toproduce a panel of, for example, 100 Da fragments. Restrictionendonucleases and their sites of action are well known to the skilledartisan. In this manner, mass spectrometry can be performed for thepurposes of restriction mapping.

[0084] Upon ionization, several peaks are observed from one sample dueto the formation of ions with different charges. Averaging the multiplereadings of molecular mass obtained from a single mass spectrum affordsan estimate of molecular mass of the bioagent. Electrospray ionizationmass spectrometry (ESI-MS) is particularly useful for very highmolecular weight polymers such as proteins and nucleic acids havingmolecular weights greater than 10 kDa, since it yields a distribution ofmultiply-charged molecules of the sample without causing a significantamount of fragmentation.

[0085] The mass detectors used in the methods of the present inventioninclude, but are not limited to, Fourier transform ion cyclotronresonance mass spectrometry (FT-ICR-MS), ion trap, quadrupole, magneticsector, time of flight (TOF), Q-TOF, and triple quadrupole.

[0086] In general, the mass spectrometric techniques which can be usedin the present invention include, but are not limited to, tandem massspectrometry, infrared multiphoton dissociation and pyrolytic gaschromatography mass spectrometry (PGC-MS). In one embodiment of theinvention, the bioagent detection system operates continually inbioagent detection mode using pyrolytic GC-MS without PCR for rapiddetection of increases in biomass (for example, increases in fecalcontamination of drinking water or of germ warfare agents). To achieveminimal latency, a continuous sample stream flows directly into thePGC-MS combustion chamber. When an increase in biomass is detected, aPCR process is automatically initiated. Bioagent presence produceselevated levels of large molecular fragments from, for example, about100-7,000 Da which are observed in the PGC-MS spectrum. The observedmass spectrum is compared to a threshold level and when levels ofbiomass are determined to exceed a predetermined threshold, the bioagentclassification process described hereinabove (combining PCR and MS, suchas FT-ICR MS) is initiated. Optionally, alarms or other processes(halting ventilation flow, physical isolation) are also initiated bythis detected biomass level.

[0087] The accurate measurement of molecular mass for large DNAs islimited by the adduction of cations from the PCR reaction to eachstrand, resolution of the isotopic peaks from natural abundance ¹³C and¹⁵N isotopes, and assignment of the charge state for any ion. Thecations are removed by in-line dialysis using a flow-through chip thatbrings the solution containing the PCR products into contact with asolution containing ammonium acetate in the presence of an electricfield gradient orthogonal to the flow. The latter two problems areaddressed by operating with a resolving power of >100,000 and byincorporating isotopically depleted nucleotide triphosphates into theDNA. The resolving power of the instrument is also a consideration. At aresolving power of 10,000, the modeled signal from the [M-14H+]¹⁴⁻charge state of an 84mer PCR product is poorly characterized andassignment of the charge state or exact mass is impossible. At aresolving power of 33,000, the peaks from the individual isotopiccomponents are visible. At a resolving power of 100,000, the isotopicpeaks are resolved to the baseline and assignment of the charge statefor the ion is straightforward. The [¹³C, ¹⁵N]-depleted triphosphatesare obtained, for example, by growing microorganisms on depleted mediaand harvesting the nucleotides (Batey et al., Nucl. Acids Res., 1992,20, 4515-4523).

[0088] While mass measurements of intact nucleic acid regions arebelieved to be adequate to determine most bioagents, tandem massspectrometry (MS^(n)) techniques may provide more definitive informationpertaining to molecular identity or sequence. Tandem MS involves thecoupled use of two or more stages of mass analysis where both theseparation and detection steps are based on mass spectrometry. The firststage is used to select an ion or component of a sample from whichfurther structural information is to be obtained. The selected ion isthen fragmented using, e.g., blackbody irradiation, infrared multiphotondissociation, or collisional activation. For example, ions generated byelectrospray ionization (ESI) can be fragmented using IR multiphotondissociation. This activation leads to dissociation of glycosidic bondsand the phosphate backbone, producing two series of fragment ions,called the w-series (having an intact 3′ terminus and a 5′ phosphatefollowing internal cleavage) and the α-Base series(having an intact 5′terminus and a 3′ furan).

[0089] The second stage of mass analysis is then used to detect andmeasure the mass of these resulting fragments of product ions. Such ionselection followed by fragmentation routines can be performed multipletimes so as to essentially completely dissect the molecular sequence ofa sample.

[0090] If there are two or more targets of similar molecular mass, or ifa single amplification reaction results in a product which has the samemass as two or more bioagent reference standards, they can bedistinguished by using mass-modifying “tags.” In this embodiment of theinvention, a nucleotide analog or “tag” is incorporated duringamplification (e.g., a 5-(trifluoromethyl) deoxythymidine triphosphate)which has a different molecular weight than the unmodified base so as toimprove distinction of masses. Such tags are described in, for example,PCT W097/33000, which is incorporated herein by reference in itsentirety. This further limits the number of possible base compositionsconsistent with any mass. For example, 5-(trifluoromethyl)deoxythymidinetriphosphate can be used in place of dTTP in a separate nucleic acidamplification reaction. Measurement of the mass shift between aconventional amplification product and the tagged product is used toquantitate the number of thymidine nucleotides in each of the singlestrands. Because the strands are complementary, the number of adenosinenucleotides in each strand is also determined.

[0091] In another amplification reaction, the number of G and C residuesin each strand is determined using, for example, the cytidine analog5-methylcytosine (5-meC) or propyne C. The combination of the A/Treaction and G/C reaction, followed by molecular weight determination,provides a unique base composition. This method is summarized in FIG. 4and Table 1. TABLE 1 Total Total Total Base Base base base Double SingleΔmass info info comp. comp. strand strand this this other Top BottomMass tag sequence sequence strand strand strand strand strand T* ΔmassT*ACGT*ACGT* T*ACGT*ACGT* 3x 3T 3A 3T 3A (T* − T) = x AT*GCAT*GCA 2A 2T2C 2G 2G 2C AT*GCAT*GCA 2x 2T 2A C* Δmass TAC*GTAC*GT TAC*GTAC*GT 2x 2C2G (C* − C) = y ATGC*ATGC*A ATGC*ATGC*A 2x 2C 2G

[0092] The mass tag phosphorothioate A (A*) was used to distinguish aBacillus anthracis cluster. The B. anthracis (A₁₄G₉C₁₄T₉) had an averageMW of 14072.26, and the B. anthracis(A₁A*₁₃G₉C₁₄T₉) had an averagemolecular weight of 14281.11 and the phosphorothioate A had an averagemolecular weight of +16.06 as determined by ESI-TOF MS. The deconvolutedspectra are shown in FIG. 5.

[0093] In another example, assume the measured molecular masses of eachstrand are 30,000.115Da and 31,000.115 Da respectively, and the measurednumber of dT and dA residues are (30,28) and (28,30). If the molecularmass is accurate to 100 ppm, there are 7 possible combinations of dG+dCpossible for each strand. However, if the measured molecular mass isaccurate to 10 ppm, there are only 2 combinations of dG+dC, and at 1 ppmaccuracy there is only one possible base composition for each strand.

[0094] Signals from the mass spectrometer may be input to amaximum-likelihood detection and classification algorithm such as iswidely used in radar signal processing. The detection processing usesmatched filtering of BCS observed in mass-basecount space and allows fordetection and subtraction of signatures from known, harmless organisms,and for detection of unknown bioagent threats. Comparison of newlyobserved bioagents to known bioagents is also possible, for estimationof threat level, by comparing their BCS to those of known organisms andto known forms of pathogenicity enhancement, such as insertion ofantibiotic resistance genes or toxin genes.

[0095] Processing may end with a Bayesian classifier using loglikelihood ratios developed from the observed signals and averagebackground levels. The program emphasizes performance predictionsculminating in probability-of-detection versusprobability-of-false-alarm plots for conditions involving complexbackgrounds of naturally occurring organisms and environmentalcontaminants. Matched filters consist of a priori expectations of signalvalues given the set of primers used for each of the bioagents. Agenomic sequence database (e.g. GenBank) is used to define the massbasecount matched filters. The database contains known threat agents andbenign background organisms. The latter is used to estimate and subtractthe signature produced by the background organisms. A maximum likelihooddetection of known background organisms is implemented using matchedfilters and a running-sum estimate of the noise covariance. Backgroundsignal strengths are estimated and used along with the matched filtersto form signatures which are then subtracted. the maximum likelihoodprocess is applied to this “cleaned up” data in a similar manneremploying matched filters for the organisms and a running-sum estimateof the noise-covariance for the cleaned up data.

[0096] F. Base Composition Signatures as Indices of Bioagent IdentifyingAmplicons

[0097] Although the molecular mass of amplification products obtainedusing intelligent primers provides a means for identification ofbioagents, conversion of molecular mass data to a base compositionsignature is useful for certain analyses. As used herein, a “basecomposition signature” (BCS) is the exact base composition determinedfrom the molecular mass of a bioagent identifying amplicon. In oneembodiment, a BCS provides an index of a specific gene in a specificorganism.

[0098] Base compositions, like sequences, vary slightly from isolate toisolate within species. It is possible to manage this diversity bybuilding “base composition probability clouds” around the compositionconstraints for each species. This permits identification of organismsin a fashion similar to sequence analysis. A “pseudo four-dimensionalplot” can be used to visualize the concept of base compositionprobability clouds (FIG. 18). Optimal primer design requires optimalchoice of bioagent identifying amplicons and maximizes the separationbetween the base composition signatures of individual bioagents. Areaswhere clouds overlap indicate regions that may result in amisclassification, a problem which is overcome by selecting primers thatprovide information from different bioagent identifying amplicons,ideally maximizing the separation of base compositions. Thus, one aspectof the utility of an analysis of base composition probability clouds isthat it provides a means for screening primer sets in order to avoidpotential misclassifications of BCS and bioagent identity. Anotheraspect of the utility of base composition probability clouds is thatthey provide a means for predicting the identity of a bioagent whoseexact measured BCS was not previously observed and/or indexed in a BCSdatabase due to evolutionary transitions in its nucleic acid sequence.

[0099] It is important to note that, in contrast to probe-basedtechniques, mass spectrometry determination of base composition does notrequire prior knowledge of the composition in order to make themeasurement, only to interpret the results. In this regard, the presentinvention provides bioagent classifying information similar to DNAsequencing and phylogenetic analysis at a level sufficient to detect andidentify a given bioagent. Furthermore, the process of determination ofa previously unknown BCS for a given bioagent (for example, in a casewhere sequence information is unavailable) has downstream utility byproviding additional bioagent indexing information with which topopulate BCS databases. The process of future bioagent identification isthus greatly improved as more BCS indexes become available in the BCSdatabases.

[0100] Another embodiment of the present invention is a method ofsurveying bioagent samples that enables detection and identification ofall bacteria for which sequence information is available using a set oftwelve broad-range intelligent PCR primers. Six of the twelve primersare “broad range survey primers” herein defined as primers targeted tobroad divisions of bacteria (for example, the Bacillus/Clostridia groupor gamma-proteobacteria). The other six primers of the group of twelveprimers are “division-wide” primers herein defined as primers whichprovide more focused coverage and higher resolution. This method enablesidentification of nearly 100% of known bacteria at the species level. Afurther example of this embodiment of the present invention is a methodherein designated “survey/drill-down” wherein a subspeciescharacteristic for detected bioagents is obtained using additionalprimers. Examples of such a subspecies characteristic include but arenot limited to: antibiotic resistance, pathogenicity island, virulencefactor, strain type, sub-species type, and lade group. Using thesurvey/drill-down method, bioagent detection, confirmation and asubspecies characteristic can be provided within hours. Moreover, thesurvey/drill-down method can be focused to identify bioengineeringevents such as the insertion of a toxin gene into a bacterial speciesthat does not normally make the toxin.

[0101] G. Fields of Application of the Present Invention

[0102] The present methods allow extremely rapid and accurate detectionand identification of bioagents compared to existing methods.Furthermore, this rapid detection and identification is possible evenwhen sample material is impure. The methods leverage ongoing biomedicalresearch in virulence, pathogenicity, drug resistance and genomesequencing into a method which provides greatly improved sensitivity,specificity and reliability compared to existing methods, with lowerrates of false positives. Thus, the methods are useful in a wide varietyof fields, including, but not limited to, those fields discussed below.

[0103] 1. Environmental and Product Testing Methods

[0104] In some embodiments of the invention, the methods disclosedherein can be used for environmental testing. “Environment” is hereindefined as including both natural environment such as soil, water,living matter such as plants, as well as environments created by humanssuch as buildings, vehicles, containers, water towers. Detection anddiscrimination of pathogenic vs. non-pathogenic bacteria, viruses,parasites, fungi and the like, in samples of water, land, air, or othersamples, can be carried out. Water samples can be obtained from, forexample, lakes, rivers, oceans, streams, water treatment systems,rainwater, groundwater, water table, reservoirs, wells, bottled water,and the like. Air samples can be obtained from ventilation systems,airplane cabins, schools, hospitals, mass transit locations such assubways, train stations, airports, and the like. Land samples can beobtained from any location.

[0105] In other embodiments of the invention, the methods disclosedherein can be used for detecting the presence of bioagents in acontainer, such as a package, box, envelope, mail tube, railroad boxcar, and the like. For example, mail and package delivery entities andagencies, both domestic and abroad, as well investigative agencies suchas the FBI and ATF can use the present methods to detect bioagents incontainers. Appropriate sampling techniques are well known to thoseskilled in the art.

[0106] In other embodiments of the invention, the methods disclosedherein can be used for detecting the presence of pathogenic andnon-pathogenic bacteria, viruses, parasites, fungi and the like inproducts. “Products” are defined as objects for consumption such asprocessed food, drinks and cosmetics. For example, food and wine can beexamined for the presence of pathogenic and non-pathogenic bacteria,viruses, parasites, fungi and the like. Particular types of foodssusceptible to bioagent contamination, such as agricultural products,meat products and eggs, can be examined for pathogenic organisms such asE. coli and Salmonella species. Such examination procedures can be usedby, for example, the wholesalers of foodstuffs and beverages, or byregulatory agencies such as the U.S. Department of Agriculture and theFood and Drug Administration. In addition, grapes and wines, forexample, can be examined using the present methods to detect particularstrains of bacteria or yeast that may indicate a particular time uponwhich to harvest the grapes or alter the wine-making process.Appropriate methods of sampling food, drink and cosmetic products arewell known to those will skill in the art.

[0107] In another embodiment, the present invention can be used forrapid detection and identification of species of household mold which isbecoming a growing concern for homeowners. Methods of sampling householdmolds are well known to those skilled in the art.

[0108] In another embodiment, the methods of the present invention canbe used to monitor bioremediation processes by detection, identificationand quantification of indigenous and bioremediating bioagents. Methodsof sampling sites of bioremediation include, but are not limited to,water and soil sampling methods which are well known to those skilled inthe art.

[0109] While the present invention has been described with specificityin accordance with certain of its embodiments, the following examplesserve only to illustrate the invention and are not intended to limit thesame.

EXAMPLES Example 1 Nucleic Acid Isolation and PCR

[0110] In one embodiment, nucleic acid is isolated from the organismsand amplified by PCR using standard methods prior to BCS determinationby mass spectrometry. Nucleic acid is isolated, for example, bydetergent lysis of bacterial cells, centrifugation and ethanolprecipitation. Nucleic acid isolation methods are described in, forexample, Current Protocols in Molecular Biology (Ausubel et al.) andMolecular Cloning; A Laboratory Manual (Sambrook et al.). The nucleicacid is then amplified using standard methodology, such as PCR, withprimers which bind to conserved regions of the nucleic acid whichcontain an intervening variable sequence as described below.

[0111] General Genomic DNA Sample Prep Protocol: Raw samples arefiltered using Supor-200 0.2 μm membrane syringe filters (VWRInternational) . Samples are transferred to 1.5 ml eppendorf tubespre-filled with 0.45 g of 0.7 mm Zirconia beads followed by the additionof 350 μl of ATL buffer (Qiagen, Valencia, Calif.). The samples aresubjected to bead beating for 10 minutes at a frequency of 19 l/s in aRetsch Vibration Mill (Retsch). After centrifugation, samples aretransferred to an S-block plate (Qiagen) and DNA isolation is completedwith a BioRobot 8000 nucleic acid isolation robot (Qiagen).

[0112] Swab Sample Protocol: Allegiance S/P brand culture swabs andcollection/transport system are used to collect samples. After drying,swabs are placed in 17×100 mm culture tubes (VWR International) and thegenomic nucleic acid isolation is carried out automatically with aQiagen Mdx robot and the Qiagen QIAamp DNA Blood BioRobot Mdx genomicpreparation kit (Qiagen, Valencia, Calif.).

Example 2 Mass Spectrometry

[0113] FTICR Instrumentation: The FTICR instrument is based on a 7 teslaactively shielded superconducting magnet and modified Bruker DaltonicsApex II 70e ion optics and vacuum chamber. The spectrometer isinterfaced to a LEAP PAL autosampler and a custom fluidics controlsystem for high throughput screening applications. Samples are analyzeddirectly from 96-well or 384-well microtiter plates at a rate of about 1sample/minute. The Bruker data-acquisition platform is supplemented witha lab-built ancillary NT datastation which controls the autosampler andcontains an arbitrary waveform generator capable of generating complexrf-excite waveforms (frequency sweeps, filtered noise, stored waveforminverse Fourier transform (SWIFT), etc.) for sophisticated tandem MSexperiments. For oligonucleotides in the 20-30-mer regime typicalperformance characteristics include mass resolving power in excess of100,000 (FWHM), low ppm mass measurement errors, and an operable m/zrange between 50 and 5000 m/z.

[0114] Modified ESI Source: In sample-limited analyses, analytesolutions are delivered at 150 nL/minute to a 30 mm i.d. fused-silicaESI emitter mounted on a 3-D micromanipulator. The ESI ion opticsconsists of a heated metal capillary, an rf-only hexapole, a skimmercone, and an auxiliary gate electrode. The 6.2 cm rf-only hexapole iscomprised of 1 mm diameter rods and is operated at a voltage of 380 Vppat a frequency of 5 MHz. A lab-built electro-mechanical shutter can beemployed to prevent the electrospray plume from entering the inletcapillary unless triggered to the “open” position via a TTL pulse fromthe data station. When in the “closed” position, a stable electrosprayplume is maintained between the ESI emitter and the face of the shutter.The back face of the shutter arm contains an elastomeric seal that canbe positioned to form a vacuum seal with the inlet capillary. When theseal is removed, a 1 mm gap between the shutter blade and the capillaryinlet allows constant pressure in the external ion reservoir regardlessof whether the shutter is in the open or closed position. When theshutter is triggered, a “time slice” of ions is allowed to enter theinlet capillary and is subsequently accumulated in the external ionreservoir. The rapid response time of the ion shutter (<25 ms) providesreproducible, user defined intervals during which ions can be injectedinto and accumulated in the external ion reservoir.

[0115] Apparatus for Infrared Multiphoton Dissociation: A 25 watt CW CO₂laser operating at 10.6 μm has been interfaced to the spectrometer toenable infrared multiphoton dissociation (IRMPD) for oligonucleotidesequencing and other tandem MS applications. An aluminum optical benchis positioned approximately 1.5 m from the actively shieldedsuperconducting magnet such that the laser beam is aligned with thecentral axis of the magnet. Using standard IR-compatible mirrors andkinematic mirror mounts, the unfocused 3 mm laser beam is aligned totraverse directly through the 3.5 mm holes in the trapping electrodes ofthe FTICR trapped ion cell and longitudinally traverse the hexapoleregion of the external ion guide finally impinging on the skimmer cone.This scheme allows IRMPD to be conducted in an m/z selective manner inthe trapped ion cell (e.g. following a SWIFT isolation of the species ofinterest), or in a broadband mode in the high pressure region of theexternal ion reservoir where collisions with neutral molecules stabilizeIRMPD-generated metastable fragment ions resulting in increased fragmention yield and sequence coverage.

Example 3 Identification of Bioagents

[0116] Table 2 shows a small cross section of a database of calculatedmolecular masses for over 9 primer sets and approximately 30 organisms.The primer sets were derived from rRNA alignment. Examples of regionsfrom rRNA consensus alignments are shown in FIGS. 1A-1C. Lines witharrows are examples of regions to which intelligent primer pairs for PCRare designed. The primer pairs are >95% conserved in the bacterialsequence database (currently over 10,000 organisms). The interveningregions are variable in length and/or composition, thus providing thebase composition “signature” (BCS) for each organism. Primer pairs werechosen so the total length of the amplified region is less than about80-90 nucleotides. The label for each primer pair represents thestarting and ending base number of the amplified region on the consensusdiagram.

[0117] Included in the short bacterial database cross-section in Table 2are many well known pathogens/biowarfare agents (shown in bold/redtypeface) such as Bacillus anthracis or Yersinia pestis as well as someof the bacterial organisms found commonly in the natural environmentsuch as Streptomyces. Even closely related organisms can bedistinguished from each other by the appropriate choice of primers. Forinstance, two low G+C organisms, Bacillus anthracis and Staph aureus,can be distinguished from each other by using the primer pair defined by16S_(—)1337 or 23S_(—)855 (ΔM of 4 Da). TABLE 2 Cross Section Of ADatabase Of Calculated Molecular Masses¹ Primer Regions Bug Name 16S_97116S_1100 16S_1337 16S_1294 16S_1228 23S_1021 23S_855 23S_193 23S_115Acinetobacter calcoaceticus 55619.1 55004 28446.7 35854.9 51295.4 3029942654 39557.5 54999

55005 54388 28448 35238 51296 30295 42651 39560 56850 Bacillus cereus55622.1 54387.9 28447.6 35854.9 51296.4 30295 42651 39560.5 56850.3Bordetella bronchiseptica 56857.3 51300.4 28446.7 35857.9 51307.4 3029942653 39559.5 51920.5 Borrelia burgdorferi 56231.2 55621.1 28440.735852.9 51295.4 30297 42029.9 38941.4 52524.6

58098 55011 28448 35854 50683 Campylobacter jejuni 58088.5 54386.929061.8 35856.9 50674.3 30294 42032.9 39558.5 45732.5

55000 55007 29063 35855 50676 30295 42036 38941 56230

55006 53767 28445 35855 51291 30300 42656 39562 54999 Clostridiumdifficile 56855.3 54386.9 28444.7 35853.9 51296.4 30294 41417.8 39556.555612.2 Enterococcus faecalis 55620.1 54387.9 28447.6 35858.9 51296.430297 42652 39559.5 56849.3

55622 55009 28445 35857 51301 30301 42656 39562 54999

53769 54385 28445 35856 51298 Haemophilus influenzae 55620.1 5500628444.7 35855.9 51298.4 30298 42656 39560.5 55613.1 Kiebsiellapneumoniae 55622.1 55008 28442.7 35856.9 51297.4 30300 42655 39562.555000

55618 55626 28446 35857 51303 Mycobacterium avium 54390.9 55631.129064.8 35858.9 51915.5 30298 42656 38942.4 56241.2 Mycobacterium leprae54389.9 55629.1 29064.8 35860.9 51917.5 30298 42656 39559.5 56240.2Mycobacterium tuberculosis 54390.9 55629.1 29064.8 35860.9 51301.4 3029942656 39560.5 56243.2 Mycoplasma genitalium 53143.7 45115.4 29061.835854.9 50671.3 30294 43264.1 39558.5 56842.4 Mycoplasma pneumoniae53143.7 45118.4 29061.8 35854.9 50673.3 30294 43264.1 39559.5 56843.4Neisseria gonorrhoeae 55627.1 54389.9 28445.7 35855.9 51302.4 3030042649 39561.5 55000

55623 55010 28443 35858 51301 30298 43272 39558 55619

58093 55621 28448 35853 50677 30293 42650 39559 53139

58094 55623 28448 35853 50679 30293 42648 39559 53755

55622 55005 28445 35857 51301 30301 42658

55623 55009 28444 35857 51301 Staphylococcus aureus 56854.3 54386.928443.7 35852.9 51294.4 30298 42655 39559.5 57466.4 Streptomyces 54389.959341.6 29063.8 35858.9 51300.4 39563.5 56864.3 Treponema pallidum56245.2 55631.1 28445.7 35851.9 51297.4 30299 42034.9 38939.4 57473.4

55625 55626 28443 35857 52536 29063 30303 35241 50675 Vibrioparahaemolyticus 54384.9 55626.1 28444.7 34620.7 50064.2

55620 55626 28443 35857 51299

[0118]FIG. 6 shows the use of ESI-FT-ICR MS for measurement of exactmass. The spectra from 46mer PCR products originating at position 1337of the 16S rRNA from S. aureus (upper) and B. anthracis (lower) areshown. These data are from the region of the spectrum containing signalsfrom the [M-8H+]⁸⁻ charge states of the respective 5′-3′ strands. Thetwo strands differ by two (AT→CG) substitutions, and have measuredmasses of 14206.396 and 14208.373+0.010 Da, respectively. The possiblebase compositions derived from the masses of the forward and reversestrands for the B. anthracis products are listed in Table 3. TABLE 3Possible base composition for B. anthracis products Calc. Mass ErrorBase Comp. 14208.2935 0.079520 A1 G17 C10 T18 14208.3160 0.056980 A1 G20C15 T10 14208.3386 0.034440 A1 G23 C20 T2 14208.3074 0.065560 A6 G11 C3T26 14208.3300 0.043020 A6 G14 C8 T18 14208.3525 0.020480 A6 G17 C13 T1014208.3751 0.002060 A6 G20 C18 T2 14208.3439 0.029060 A11 G8 C1 T2614208.3665 0.006520 A11 G11 C6 T18 14208.3890 0.016020 A11 G14 C11 T1014208.4116 0.038560 A11 G17 C16 T2 14208.4030 0.029980 A16 G8 C4 T1814208.4255 0.052520 A16 G11 C9 T10 14208.4481 0.075060 A16 G14 C14 T214208.4395 0.066480 A21 G5 C2 T18 14208.4620 0.089020 A21 G8 C7 T1014079.2624 0.080600 A0 G14 C13 T19 14079.2849 0.058060 A0 G17 C18 T1114079.3075 0.035520 A0 G20 C23 T3 14079.2538 0.089180 A5 G5 C1 T3514079.2764 0.066640 A5 G8 C6 T27 14079.2989 0.044100 A5 G11 C11 T1914079.3214 0.021560 A5 G14 C16 T11 14079.3440 0.000980 A5 G17 C21 T314079.3129 0.030140 A10 G5 C4 T27 14079.3354 0.007600 A10 G8 C9 T1914079.3579 0.014940 A10 G11 C14 T11 14079.3805 0.037480 A10 G14 C19 T314079.3494 0.006360 A15 G2 C2 T27 14079.3719 0.028900 A15 G5 C7 T1914079.3944 0.051440 A15 G8 C12 T11 14079.4170 0.073980 A15 G11 C17 T314079.4084 0.065400 A20 G2 C5 T19 14079.4309 0.087940 A20 G5 C10 T13

[0119] Among the 16 compositions for the forward strand and the 18compositions for the reverse strand that were calculated, only one pair(shown in bold) are complementary, corresponding to the actual basecompositions of the B. anthracis PCR products.

Example 4 BCS of Region from Bacillus anthracis and Bacillus cereus

[0120] A conserved Bacillus region from B. anthracis (A₁₄G₉C₁₄T₉) and B.cereus(A₁₅G₉Cl₁₃T₉) having a C to A base change was synthesized andsubjected to ESI-TOF MS. The results are shown in FIG. 7 in which thetwo regions are clearly distinguished using the method of the presentinvention (MW=14072.26 vs. 14096.29).

Example 5 Identification of Additional Bioagents

[0121] In other examples of the present invention, the pathogen Vibriocholera can be distinguished from Vibrio parahemolyticus with ΔM>600 Dausing one of three 16S primer sets shown in Table 2 (16S_(—)971,16S_(—)1228 or 16S_(—)1294) as shown in Table 4. The two mycoplasmaspecies in the list (M. genitalium and M. pneumoniae) can also bedistinguished from each other, as can the three mycobacteriae. While thedirect mass measurements of amplified products can identify anddistinguish a large number of organisms, measurement of the basecomposition signature provides dramatically enhanced resolving power forclosely related organisms. In cases such as Bacillus anthracis andBacillus cereus that are virtually indistinguishable from each otherbased solely on mass differences, compositional analysis orfragmentation patterns are used to resolve the differences. The singlebase difference between the two organisms yields different fragmentationpatterns, and despite the presence of the ambiguous/unidentified base Nat position 20 in B. anthracis, the two organisms can be identified.

[0122] Tables 4a-b show examples of primer pairs from Table 1 whichdistinguish pathogens from background. TABLE 4a Organism name 23S_85516S_1337 23S_1021 Bacillus anthracis 42650.98 28447.65 30294.98Staphylococcus aureus 42654.97 28443.67 30297.96

[0123] TABLE 4b Organism name 16S_971 16S_1294 16S_1228 Vibrio cholerae55625.09 35856.87 52535.59 Vibrio parahaemolyticus 54384.91 34620.6750064.19

[0124] Table 5 shows the expected molecular weight and base compositionof region 16S_(—)1100-1188 in Mycobacterium avium and Streptomyces sp.TABLE 5 Organism Molecular Region name Length weight Base comp. 16S_(—)Mycobacterium 82 25624.1728 A₁₆G₃₂C₁₈T₁₆ 1100-1188 avium 16S_(—)Streptomyces 96 29904.871 A₁₇G₃₈C₂₇T₁₄ 1100-1188 sp.

[0125] Table 6 shows base composition (single strand) results for16S_(—)1100-1188 primer amplification reactions different species ofbacteria. Species which are repeated in the table (e.g., Clostridiumbotulinum) are different strains which have different base compositionsin the 16S_(—)1100- 1188 region. TABLE 6 Organism name Base comp.Organism name Base comp. Mycobacterium avium A₁₆G₃₂C₁₈T₁₆ Vibriocholerae A₂₃G₃₀C₂₁T₁₆ Streptomyces sp. A₁₇G₃₈C₂₇T₁₄

A ₂₃ G ₃₁ C ₂₁ T ₁₅ Ureaplasma urealyticum A₁₈G₃₀C₁₇T₁₇

A ₂₃ G ₃₁ C ₂₁ T ₁₅ Streptomyces sp. A₁₉G₃₆C₂₄T₁₈ Mycoplasma genitaliumA₂₄G₁₉C₁₂T₁₈ Mycobacterium leprae A₂₀G₃₂C₂₂T₁₆ Clostridium botulinumA₂₄G₂₅C₁₈T₂₀

A ₂₀ G ₃₃ C ₂₁ T ₁₆ Bordetella bronchiseptica A₂₄G₂₆C₁₉T₁₄

A ₂₀ G ₃₃ C ₂₁ T ₁₆ Francisella tularensis A₂₄G₂₆C₁₉T₁₉ Fusobacteriumnecroforum A₂₁G₂₆C₂₂T₁₆

A ₂₄ G ₂₆ C ₂₀ T ₁₈ Listeria monocytogenes A₂₁G₂₇C₁₉T₁₉

A ₂₄ G ₂₆ C ₂₀ T ₁₈ Clostridium botulinum A₂₁G₂₇C₁₉T₂₁

A ₂₄ G ₂₆ C ₂₀ T ₁₈ Neisseria gonorrhoeae A₂₁G₂₈C₂₁T₁₈ Helicobacterpylori A₂₄G₂₆C₂₀T₁₉ Bartonella quintana A₂₁G₃₀C₂₂T₁₆ Helicobacter pyloriA₂₄G₂₆C₂₁T₁₈ Enterococcus faecalis A₂₂G₂₇C₂₀T₁₉ Moraxella catarrhalisA₂₄G₂₆C₂₃T₁₆ Bacillus megaterium A₂₂G₂₈C₂₀T₁₈ Haemophilus influenzae RdA₂₄G₂₈C₂₀T₁₇ Bacillus subtilis A₂₂G₂₈C₂₁T₁₇

A ₂₄ G ₂₈ C ₂₁ T ₁₆ Pseudomonas aeruginosa A₂₂G₂₉C₂₃T₁₅

A ₂₄ G ₂₈ C ₂₁ T ₁₆ Legionella pneumophila A₂₂G₃₂C₂₀T₁₆

A ₂₄ G ₂₈ C ₂₁ T ₁₆ Mycoplasma pneumoniae A₂₃G₂₀C₁₄T₁₆ Pseudomonasputida A₂₄G₂₉C₂₁T₁₆ Clostridium botulinum A₂₃G₂₆C₂₀T₁₉

A ₂₄ G ₃₀ C ₂₁ T ₁₅ Enterococcus faecium A₂₃G₂₆C₂₁T₁₈

A ₂₄ G ₃₀ C ₂₁ T ₁₅ Acinetobacter calcoaceti A₂₃G₂₆C₂₁T₁₉

A ₂₄ G ₃₀ C ₂₁ T ₁₅

A ₂₃ G ₂₆ C ₂₄ T ₁₅ Clostridium botulinum A₂₅G₂₄C₁₈T₂₁

A ₂₃ G ₂₆ C ₂₄ T ₁₅ Clostridium tetani A₂₅G₂₅C₁₈T₂₀ Clostridiumperfringens A₂₃G₂₇C₁₉T₁₉ Francisella tularensis A₂₅G₂₅C₁₉T₁₉

A ₂₃ G ₂₇ C ₂₀ T ₁₈ Acinetobacter calcoacetic A₂₅G₂₆C₂₀T₁₉

A ₂₃ G ₂₇ C ₂₀ T ₁₈ Bacteriodes fragilis A₂₅G₂₇C₁₆T₂₂

A ₂₃ G ₂₇ C ₂₀ T ₁₈ Chlamydophila psittaci A₂₅G₂₇C₂₁T₁₆ Aeromonashydrophila A₂₃G₂₉C₂₁T₁₆ Borrelia burgdorferi A₂₅G₂₉C₁₇T₁₉ Escherichiacoli A₂₃G₂₉C₂₁T₁₆ Streptobacillus monilifor A₂₆G₂₆C₂₀T₁₆ Pseudomonasputida A₂₃G₂₉C₂₁T₁₇ Rickettsia prowazekii A₂₆G₂₈C₁₈T₁₈

A ₂₃ G ₂₉ C ₂₂ T ₁₅ Rickettsia rickettsii A₂₆G₂₈C₂₀T₁₆

A ₂₃ G ₂₉ C ₂₂ T ₁₅ Mycoplasma mycoides A₂₈G₂₃C₁₆T₂₀

[0126] The same organism having different base compositions aredifferent strains. Groups of organisms which are highlighted or initalics have the same base compositions in the amplified region. Some ofthese organisms can be distinguished using multiple primers. Forexample, Bacillus anthracis can be distinguished from Bacillus cereusand Bacillus thuringiensis using the primer 16S_(—)971-1062 (Table 7).Other primer pairs which produce unique base composition signatures areshown in Table 6 (bold). Clusters containing very similar threat andubiquitous non-threat organisms (e.g. anthracis cluster) aredistinguished at high resolution with focused sets of primer pairs. Theknown biowarfare agents in Table 6 are Bacillus anthracis, Yersiniapestis, Francisella tularensis and Rickettsia prowazekii. TABLE 7Organism 16S_971-1062 16S_1228-1310 16S_1100-1188 Aeromonas hydrophilaA₂₁G₂₉C₂₂T₂₀ A₂₂G₂₇C₂₁T₁₃ A₂₃G₃₁C₂₁T₁₅ Aeromonas salmonicidaA₂₁G₂₉C₂₂T₂₀ A₂₂G₂₇C₂₁T₁₃ A₂₃G₃₁C₂₁T₁₅ Bacillus anthracis A ₂₁ G ₂₇ C ₂₂T ₂₂ A₂₄G₂₂C₁₉T₁₈ A₂₃G₂₇C₂₀T₁₈ Bacillus cereus A₂₂G₂₇C₂₁T₂₂ A₂₄G₂₂C₁₉T₁₈A₂₃G₂₇C₂₀T₁₈ Bacillus thuringiensis A₂₂G₂₇C₂₁T₂₂ A₂₄G₂₂C₁₉T₁₈A₂₃G₂₇C₂₀T₁₈ Chlamydia trachomatis A ₂₂ G ₂₆ C ₂₀ T ₂₃ A ₂₄ G ₂₃ C ₁₉ T₁₆ A₂₄G₂₈C₂₁T₁₆ Chlamydia pneumoniae AR39 A₂₆G₂₃C₂₀T₂₂ A₂₆G₂₂C₁₆T₁₈A₂₄G₂₈C₂₁T₁₆ Leptospira borgpetersenii A₂₂G₂₆C₂₀T₂₁ A₂₂G₂₅C₂₁T₁₅A₂₃G₂₆C₂₄T₁₅ Leptospira interrogans A₂₂G₂₆C₂₀T₂₁ A₂₂G₂₅C₂₁T₁₅A₂₃G₂₆C₂₄T₁₅ Mycoplasma genitalium A₂₈G₂₃C₁₅T₂₂ A ₃₀ G ₁₈ C ₁₅ T ₁₉ A ₂₄G ₁₉ C ₁₂ T ₁₈ Mycoplasma pneumnoniae A₂₈G₂₃C₁₅T₂₂ A ₂₇ G ₁₉ C ₁₆ T ₂₀ A₂₃ G ₂₀ C ₁₄ T ₁₆ Escherichia coli A ₂₂ G ₂₈ C ₂₀ T ₂₂ A₂₄G₂₅C₂₁T₁₃A₂₃G₂₉C₂₂T₁₅ Shigella dysenteriae A ₂₂ G ₂₈ C ₂₁ T ₂₁ A₂₄G₂₅C₂₁T₁₃A₂₃G₂₉C₂₂T₁₅ Proteus vulgaris A ₂₃ G ₂₆ C ₂₂ T ₂₁ A ₂₆ G ₂₄ C ₁₉ T ₁₄A₂₄G₃₀C₂₁T₁₅ Yersinia pestis A₂₄G₂₅C₂₁T₂₂ A₂₅G₂₄C₂₀T₁₄ A₂₄G₃₀C₂₁T₁₅Yersinia pseudotuberculosis A₂₄G₂₅C₂₁T₂₂ A₂₅G₂₄C₂₀T₁₄ A₂₄G₃₀C₂₁T₁₅Francisella tularensis A ₂₀ G ₂₅ C ₂₁ T ₂₃ A ₂₃ G ₂₆ C ₁₇ T ₁₇ A ₂₄ G ₂₆C ₁₉ T ₁₉ Rickettsia prowazekii A ₂₁ G ₂₆ C ₂₄ T ₂₅ A ₂₄ G ₂₃ C ₁₆ T ₁₉A ₂₆ G ₂₈ C ₁₈ T ₁₈ Rickettsia rickettsii A ₂₁ G ₂₆ C ₂₅ T ₂₄ A ₂₄ G ₂₄C ₁₇ T ₁₇ A ₂₆ G ₂₈ C ₂₀ T ₁₆

[0127] The sequence of B. anthracis and B. cereus in region 16S_(—)971is shown below. Shown in bold is the single base difference between thetwo species which can be detected using the methods of the presentinvention. B. anthracis has an ambiguous base at position 20. B.anthracis_16S_971 GCGAAGAACCUUACCAGGUNUUGACAUCCUCUGACAA (SEQ ID NO:1)CCCUAGAGAUAGGGCUUCUCCUUCGGGAGCAGAGUGA CAGGUGGUGCAUGGUU B. cereus_16S_971GCGAAGAACCUUACCAGGUCUUGACAUCCUCUGAAAA (SEQ ID NO:2)CCCUAGAGAUAGGGCUUCUCCUUCGGGAGCAGAGUGA CAGGUGGUGCAUGGUU

Example 6 ESI-TOF MS of sspE 56-mer Plus Calibrant

[0128] The mass measurement accuracy that can be obtained using aninternal mass standard in the ESI-MS study of PCR products is shown inFIG. 8. The mass standard was a 20-mer phosphorothioate oligonucleotideadded to a solution containing a 56-mer PCR product from the B.anthracis spore coat protein sspE. The mass of the expected PCR productdistinguishes B. anthracis from other species of Bacillus such as B.thuringiensis and B. cereus.

Example 7 B. anthracis ESI-TOF Synthetic 16S_(—)1228 Duplex

[0129] An ESI-TOF MS spectrum was obtained from an aqueous solutioncontaining 5 μM each of synthetic analogs of the expected forward andreverse PCR products from the nucleotide 1228 region of the B. anthracis16S rRNA gene. The results (FIG. 9) show that the molecular weights ofthe forward and reverse strands can be accurately determined and easilydistinguish the two strands. The [M-21H⁺]²¹⁻ and [M-20H⁺]²⁰⁻ chargestates are shown.

Example 8 ESI-FTICR-MS of Synthetic B. anthracis 16S_(—)1337 46 BasePair Duplex

[0130] An ESI-FTICR-MS spectrum was obtained from an aqueous solutioncontaining 5 μM each of synthetic analogs of the expected forward andreverse PCR products from the nucleotide 1337 region of the B. anthracis16S rRNA gene. The results (FIG. 10) show that the molecular weights ofthe strands can be distinguished by this method. The [M-16H⁺]¹⁶⁻ through[M-10H⁺]¹⁰⁻ charge states are shown. The insert highlights theresolution that can be realized on the FTICR-MS instrument, which allowsthe charge state of the ion to be determined from the mass differencebetween peaks differing by a single 13C substitution.

Example 9 ESI-TOF MS of 56-mer Oligonucleotide from saspB Gene of B.anthracis with Internal Mass Standard

[0131] ESI-TOF MS spectra were obtained on a synthetic 56-meroligonucleotide (5 μM) from the saspB gene of B. anthracis containing aninternal mass standard at an ESI of 1.7 μL/min as a function of sampleconsumption. The results (FIG. 11) show that the signal to noise isimproved as more scans are summed, and that the standard and the productare visible after only 100 scans.

Example 10 ESI-TOF MS of an Internal Standard with Tributylammonium(TBA)-trifluoroacetae (TFA) Buffer

[0132] An ESI-TOF-MS spectrum of a 20-mer phosphorothioate mass standardwas obtained following addition of 5 mM TBA-TFA buffer to the solution.This buffer strips charge from the oligonucleotide and shifts the mostabundant charge state from [M-8H⁺]⁸⁻ to [M-3H⁺]³⁻ (FIG. 12).

Example 11 Master Database Comparison

[0133] The molecular masses obtained through Examples 1-10 are comparedto molecular masses of known bioagents stored in a master database toobtain a high probability matching molecular mass.

Example 12 Master Data Base Interrogation over the Internet

[0134] The same procedure as in Example 11 is followed except that thelocal computer did not store the Master database. The Master database isinterrogated over an internet connection, searching for a molecular massmatch.

Example 13 Master Database Updating

[0135] The same procedure as in example 11 is followed except the localcomputer is connected to the internet and has the ability to store amaster database locally. The local computer system periodically, or atthe user's discretion, interrogates the Master database, synchronizingthe local master database with the global Master database. This providesthe current molecular mass information to both the local database aswell as to the global Master database. This further provides more of aglobalized knowledge base.

Example 14 Global Database Updating

[0136] The same procedure as in example 13 is followed except there arenumerous such local stations throughout the world. The synchronizationof each database adds to the diversity of information and diversity ofthe molecular masses of known bioagents.

Example 15 Environmental Sampling Protocol for Anthrax Spores UsingNon-Cotton Swabs

[0137] The use of non-cotton, sterile swabs to collect environmentalsamples is the preferred method because it reduces the amount of normalbackground contamination and improves the recovery of anthrax spores(see, for example,www.dhmh.state.md.us/labs/html/Terrorism/Biological/BT_env_samp_prtcl.html).

[0138] The following protocol is used to collect samples from smallnon-porous surfaces or objects for culture and identification ofBacillus anthracis. Non-powdered gloves, a disposable gown, and facemaskare worn during the collection of swab samples from the environment. Asterile Dacron or Rayon dry swab (non-cotton swab) is used to collectenvironmental samples. Alternatively, a swab moistened with sterilesaline or distilled water is used to collect samples from computerkeyboards, desks, mail sorting areas, and other sites within a buildingor work facility. A separate swab is used for each site. In an open area(desks, work table, mail sorting area, etc.) a swab is taken of a 10×10inch square area per swab. Each swab is placed in a 15 ml sterile tube,the shaft of swab is snapped off at the lip of the tube, and the tube isclosed. Each tube is labeled appropriately and placed in a self-sealableplastic bag. Multiple tubes can be placed in the same bag. Each tube islabeled with the date, facility location, and sampling site. The outsideof the sealed bag is cleaned by wiping with 10% bleach solution. Placeclean, sealed bags into an unused similar self-sealing bag beforedelivery. Appropriate chain-of-custody documentation and procedure isconstantly maintained.

Example 16 Environmental Sampling Protocol for Microbial Soil Samples

[0139] Soil cores are collected to a depth of 8 cm, using an 8 cmdiameter soil corer. Soils for analysis of root biomass and compositionare collected separately. A single 3.5 cm diameter core is collected toa depth of 16 cm. Three 3.5 cm cores are also taken. These cores aredivided into 0-1, 1-8, and 8-16 cm depth increments. Polyethylene bagscontaining soil cores are handled to minimize disturbance and changes insoil moisture and temperature. While sampling, any unusual features ofthe area where the core was taken are noted. Microbial Group soil coresare sieved (4 mm) and the plant material discarded.

Example 17 Estimation of the Sensitivity of Detection of Spores in WaterSamples

[0140] In order to determine the detection limits of the system againstorganisms whose genetic material is difficult to extract, dilution toextinction experiments were performed using Bacillis thuringiensisisraeliensis (Bti) spores. Highly purified spores were added to water atconcentrations that would give between 0 and 1×10⁵ spores per PCRreaction. Samples were subjected to a lysis protocol. Genomic materialwas isolated on a Qiagen 8000 Biorobot using a modified robotic versionof the DNeasy protocol from Qiagen. The DNeasy protocol was optimizedfor bacterial lysis with the addition of lysozyme and was modified foruse on the BioRobot 8000. PCR reactions were assembled using intelligentprimers for bacteria.

[0141] These reactions were set up to run automatically using a PerkinElmer MPII robot with an additional gripper arm. Automated genomeisolation, reaction setup, and subsequent PCR of the samples results inthe production of uniform, reproducible amounts of amplicon material.PCR products were desalted and purified using a recently publishedprocedure (Jiang, Y. and S. A. Hofstadler, Anal. Biochem., 2002 inpress) and were analyzed by electrospray ionization (ESI)-FTICR massspectrometry. FIG. 18 shows the spectra resulting from a single primerpair at each concentration of Bti spores used. Using a maximumlikelihood processor, we reproducibly detected Bti genomic material insamples containing as few as 100 spores. This processor readily detectssignals that are not easily discernable relative to the noise by eye.Similar results were obtained from the processing of Bacillus anthracis(Sterne strain) spores (data not shown).

Example 18 Identification of Bioagents in Air Samples.

[0142] Multi-hour air samples from indoor or outdoor air were obtainedusing a Spin-Con sampler which can sample up to 18×10⁶ L of air. The airsamples were processed as 10 ml samples and spiked with Bacillisanthracis spores or Bacillis thuringiensis israeliensis (Bti) spores.The samples were filtered and lysed via bead-beating. Nucleic acids wereisolated from the samples by standard methods and amplified by PCR usingintelligent primers. Samples were then desalted and analyzed by FT-ICRmass spectrometry according to methods outlined in example 2. Analysisof the molecular masses enabled detection and identification of theBacillis anthracis spores or Bacillis thuringiensis israeliensis (Bti)spores. FIG. 19 is an ROC curve that indicates that a spore spikedsample (Pd sample threat) is easily distinguished from backgroundbioagents (Pfa sample threat and Pfa system). The data set indicatesthat the present method of air sample detection and identification ofbioagents provides a reliable means of air sample surveillance.

[0143] Various modifications of the invention, in addition to thosedescribed herein, will be apparent to those skilled in the art from theforegoing description. Such modifications are also intended to fallwithin the scope of the appended claims. Each reference cited in thepresent application is incorporated herein by reference in its entirety

1 4 1 90 RNA Bacillus anthracis misc_feature (20)..(20) N = A, U, G or C1 gcgaagaacc uuaccaggun uugacauccu cugacaaccc uagagauagg gcuucuccuu 60cgggagcaga gugacaggug gugcaugguu 90 2 90 RNA Bacillus cereus 2gcgaagaacc uuaccagguc uugacauccu cugaaaaccc uagagauagg gcuucuccuu 60cgggagcaga gugacaggug gugcaugguu 90 3 1542 RNA Artificial Sequencemisc_feature 16S rRNA consensus sequence 3 nnnnnnnaga guuugaucnuggcucagnnn gaacgcuggc ggnnngcnun anacaugcaa 60 gucgancgnn nnnnnnnnnnnnnnnnnnnn nnnnnnnnnn agnggcnnac gggugaguaa 120 nncnunnnna nnunccnnnnnnnnnggnan annnnnnnga aannnnnnnu aauaccnnau 180 nnnnnnnnnn nnnnaaagnnnnnnnnnnnn nnnnnnnnnn nnnnnngann nnnnnnngnn 240 nnaunagnun guuggunngguaanggcnna ccaagncnnn gannnnuagc ngnncugaga 300 ggnngnncng ccacanuggnacugaganac ggnccanacu ccuacgggag gcagcagunn 360 ggaaunuunn ncaauggnngnaanncugan nnagcnannc cgcgugnnng anganggnnu 420 nnngnungua aannncununnnnnnngang annnnnnnnn nnnnnnnnnn nnnnnnnnnu 480 gacnnuannn nnnnannaagnnncggcnaa cuncgugcca gcagccgcgg uaauacgnag 540 gnngcnagcg uunnncgganunanugggcg uaaagngnnn gnaggnggnn nnnnnngunn 600 nnngunaaan nnnnnngcunaacnnnnnnn nnncnnnnnn nacnnnnnnn cungagnnnn 660 nnagnggnnn nnngaauunnnnguguagng gugnaauncg naganaunng nangaanacc 720 nnungcgaag gcnnnnnncuggnnnnnnac ugacncunan nnncgaaagc nugggnagcn 780 aacaggauua gauacccugguaguccangc nnuaaacgnu gnnnnnunnn ngnnngnnnn 840 nnnnnnnnnn nnnnnnnnnannnaacgnnn uaannnnncc gccuggggag uacgnncgca 900 agnnunaaac ucaaangaauugacggggnc cngcacaagc ngnggagnau guggnuuaau 960 ucgangnnac gcgnanaaccuuaccnnnnn uugacaunnn nnnnnnnnnn nnganannnn 1020 nnnnnnnnnn nnnnnnnnnnnnnacaggug nugcauggnu gucgucagcu cgugnnguga 1080 gnuguugggu uaagucccgnaacgagcgca acccnnnnnn nnnguuncna ncnnnnnnnn 1140 ngngnacucn nnnnnnacugccnnngnnaa nnnggaggaa ggnggggang acgucaanuc 1200 nucaugnccc uuangnnnngggcuncacac nuncuacaau ggnnnnnaca nngngnngcn 1260 annnngnnan nnnnagcnaancnnnnaaan nnnnucnnag uncggaungn nnncugcaac 1320 ucgnnnncnu gaagnngganucgcuaguaa ucgnnnauca gnangnnncg gugaauacgu 1380 ucncgggncu uguacacaccgcccgucann ncangnnagn nnnnnnnncc nnaagnnnnn 1440 nnnnnnncnn nnnngnnnnnnnnnncnang gnnnnnnnnn nganugggnn naagucguaa 1500 caagguancc nuannngaannugnggnugg aucaccuccu un 1542 4 2904 RNA Artificial Sequencemisc_feature 23S rRNA consensus sequence 4 nnnnaagnnn nnaagngnnnnngguggaug ccunggcnnn nnnagncgan gaaggangnn 60 nnnnncnncn nnanncnnnggnnagnngnn nnnnnncnnn nnanccnnng nunuccgaau 120 ggggnaaccc nnnnnnnnnnnnnnnnnnan nnnnnnnnnn nnnnnnnnnn nnnnnnngnn 180 nacnnnnnga anugaaacaucunaguannn nnaggaanag aaannaannn ngauuncnnn 240 nguagnggcg agcgaannngnannagncnn nnnnnnnnnn nnnnnnnnnn nnnannngaa 300 nnnnnuggna agnnnnnnnnnannngguna nannccngua nnnnaaannn nnnnnnnnnn 360 nnnnnnnnnn aguannncnnnncncgngnn annnngunng aannngnnnn gaccannnnn 420 naagncuaaa uacunnnnnnngaccnauag ngnannagua cngugangga aaggngaaaa 480 gnacccnnnn nangggagugaaanagnncc ugaaaccnnn nncnuanaan nngunnnagn 540 nnnnnnnnnn nnnuganngcgunccuuuug nannaugnnn cngnganuun nnnunnnnng 600 cnagnuuaan nnnnnnnngnagncgnagng aaancgagun nnaanngngc gnnnagunnn 660 nngnnnnaga cncgaancnnngugancuan nnaugnncag gnugaagnnn nnguaanann 720 nnnuggaggn ccgaacnnnnnnnnguugaa aannnnnngg augannugug nnungnggng 780 aaanncnaan cnaacnnngnnauagcuggu ucucnncgaa annnnuuuag gnnnngcnun 840 nnnnnnnnnn nnnnggngguagagcacugn nnnnnnnnng gnnnnnnnnn nnnnuacnna 900 nnnnnnnnaa acuncgaaunccnnnnnnnn nnnnnnnngn agnnanncnn ngngngnuaa 960 nnuncnnngu nnanagggnaacancccaga ncnncnnnua aggncccnaa nnnnnnnnua 1020 aguggnaaan gangugnnnnnncnnanaca nnnaggangu uggcuuagaa gcagccancn 1080 uunaaagann gcguaanagcucacunnucn agnnnnnnng cgcngannau nuancgggnc 1140 uaannnnnnn nccgaannnnnngnnnnnnn nnnnnnnnnn nnnnngguag nngagcgunn 1200 nnnnnnnnnn ngaagnnnnnnngnnannnn nnnuggannn nnnnnnagug ngnaugnngn 1260 naunaguanc gannnnnnnngugananncn nnnncnccgn annncnaagg nuuccnnnnn 1320 nangnunnuc nnnnnngggunagucgnnnc cuaagnngag ncnganangn nuagnngaug 1380 gnnannnggu nnauauuccnnnacnnnnnn nnnnnnnnnn nnnnngacgn nnnnngnnnn 1440 nnnnnnnnnn nnnnggnnnnnnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1500 nnnnnnnnnn nnnnnnnnnnnnnnnnnnnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1560 nnnncnngaa aannnnnnnnnnnnnnnnnn nnnnnnnnnc guaccnnaaa ccgacacagg 1620 ungnnnngnn gagnanncnnaggngnnngn nnnaannnnn nnnaaggaac unngcaaanu 1680 nnnnccguan cuucggnanaaggnnnncnn nnnnnnnnnn nnnnnnnnnn nnnnnnnnnn 1740 nnnnnnnnng nnnnannnannngnnnnnnn cnacuguuua nnaaaaacac agnncnnugc 1800 naanncgnaa gnnganguauanggnnugac nccugcccng ugcnngaagg uuaanngnnn 1860 nnnnnngnnn nngnnnnnnnnnnnannnaa gcccnnguna acggcggnng uaacuauaac 1920 nnuccuaagg uagcgaaauuccuugucggg uaaguuccga ccngcacgaa nggngnaang 1980 annnnnnnnc ugucucnnnnnnnnncncng ngaanuunna nunnnnguna agaugcnnnn 2040 uncncgcnnn nngacggaaagaccccnngn ancuuuacun nannnunnna nugnnnnnnn 2100 nnnnnnnnug unnagnauaggunggagncn nngannnnnn nncgnnagnn nnnnnggagn 2160 cnnnnnugnn auacnacncunnnnnnnnnn nnnnucuaac nnnnnnnnnn nancnnnnnn 2220 nnngacanug nnngnngggnaguuunacug gggcggunnc cuccnaaann guaacggagg 2280 ngnncnaagg unnncunannnnggnnggnn aucnnnnnnn nagunnaann gnanaagnnn 2340 gcnunacugn nagnnnnacnnnncgagcag nnncgaaagn nggnnnuagu gauccggngg 2400 unnnnnnugg aagngccnucgcucaacgga uaaaagnuac ncnggggaua acaggcunau 2460 nnnncccaag aguncanaucgacggnnnng uuuggcaccu cgaugucggc ucnucncauc 2520 cuggggcugn agnnggucccaagggunngg cuguucgccn nuuaaagngg nacgngagcu 2580 ggguunanaa cgucgugagacaguungguc ccuaucngnn gngngngnnn gannnuugan 2640 nngnnnugnn cnuaguacgagaggaccggn nngnacnnan cncuggugnn ncnguugunn 2700 ngccannngc anngcngnnuagcuannunn ggnnnngaua anngcugaan gcaucuaagn 2760 nngaancnnn cnnnnagannagnnnucncn nnnnnnnnnn nnnnnnnnna gnnncnnnnn 2820 agannannnn gungauaggnnngnnnugna agnnnngnna nnnnunnagn nnacnnnuac 2880 uaaunnnncn nnnnncuunnnnnn 2904

What is claimed is:
 1. A method of identifying a bioagent in a samplecomprising the steps of: determining a first molecular mass of a firstamplification product of a first bioagent identifying amplicon from thesample and comparing the first molecular mass to a second molecular massof a second bioagent identifying amplicon, wherein both first and secondbioagent identifying amplicons are correlative.
 2. A method of claim 1wherein the sample is an environmental sample.
 3. A method of claim 2wherein the environmental sample is an air sample.
 4. A method of claim2 wherein the environmental sample is a water sample.
 5. A method ofclaim 2 wherein the environmental sample is a soil sample.
 6. A methodof claim 2 wherein the environmental sample is a surface swab sample. 7.A method of claim 2 wherein the environmental sample is from a buildingor a container.
 8. A method of claim 1 wherein the sample is a productsample.
 9. A method of claim 8 wherein the product sample is afoodstuff.
 10. A method of claim 8 wherein the product sample is acosmetic.
 11. A method of claim 1 wherein the second molecular mass ofthe second bioagent identifying amplicon is indexed to a definedbioagent and contained in a database.
 12. A method of claim 1 wherein afirst base composition signature is determined from the first molecularmass of the first amplification product and wherein the first basecomposition signature is compared to a second base composition signaturedetermined for the second bioagent identifying amplicon.
 13. A method ofclaim 12 wherein the second base composition signature is indexed to adefined bioagent and contained in a database.
 14. A method of claim 1wherein the molecular mass of the amplification product is determined byESI-TOF mass spectrometry.
 15. A method of claim 1 wherein the molecularmass of the amplification product is determined by ESI-FTICR massspectrometry.
 16. A method of claim 15 wherein a mass spectrum obtainedin determination of the molecular mass provides a measure of thequantity of the bioagent in the sample.
 17. A method of claim 1 whereinthe bioagent is a bacterium, virus, mold, fungus or parasite.
 18. Themethod of claim 17 wherein the mold is a household mold.
 19. The methodof claim 18 wherein the household mold is Stachybotrys, Cladosporium,Penicillium, or Alternaria.
 20. A method of monitoring a bioremediationprocess by identifying bioagents in a sample comprising the steps of:determining a first molecular mass of a first amplification product of afirst bioagent identifying amplicon from the sample and comparing thefirst molecular mass to a second molecular mass of a second bioagentidentifying amplicon wherein, both first and second bioagent identifyingamplicons are correlative.
 21. A method of claim 20 wherein the secondmolecular mass of the second bioagent identifying amplicon is indexed toa defined bioagent and contained in a database.
 22. A method of claim 20wherein a first base composition signature is determined from the firstmolecular mass of the first amplification product and wherein the firstbase composition signature is compared to a second base compositionsignature determined for the second bioagent identifying amplicon.
 23. Amethod of claim 22 wherein the second base composition signature isindexed to a defined bioagent and contained in a database.
 24. A methodof claim 20 wherein the molecular mass of the amplification product isdetermined by ESI-TOF mass spectrometry.
 25. A method of claim 20wherein the molecular mass of the amplification product is determined byESI-FTICR mass spectrometry.
 26. A method of claim 25 wherein a massspectrum obtained in determination of the molecular mass provides ameasure of the quantity of the bioagent in the sample.
 27. A method ofclaim 20 wherein the bioagent is a bacterium or a fungus.